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Using Proximity and Homophily to Connect Conference Attendees in a Mobile Social Network

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  • 1. Using Proximity andHomophily to ConnectConference Attendees ina Mobile Social NetworkAlvin ChinMobile Social Experiences TeamNRC Growth Economies LabNokia Research CenterNokia Research Center
  • 2. Outline • Motivation and research problem • Contributions • Find & Connect @ UbiComp 2011 • User behaviour analysis • Implications • Conclusions and future workNokia Research Center2 Company Confidential
  • 3. Motivation • Who should I meet at the conference? • Who is this person that I met? • Why should I add this person to my social network?Nokia Research Center3 Company Confidential
  • 4. Homophily • Social selection • We connect with people who are similar to us as friends (McPherson et al, 2001) • User similarity using people, places, things (Guy et al, 2010)Nokia Research Center4 Company Confidential
  • 5. Proximity • Using location and human mobility for friendship (Cho et al, 2011) • Encounters to determine who to add as friend (Aka- Aki; Quercia and Capra, 2009) • Introduce people and infer one’s social network (Eagle and Pentland, 2005) • Enhancing social interactions at conferences (Barrat et al, 2010)Nokia Research Center5 Company Confidential
  • 6. Drawback • Fail to help users create and maintain their social network at the same time to bring convenience and facilities to usersNokia Research Center6 Company Confidential
  • 7. Research problem • Determine how to use proximity and homophily to connect attendees in a conferenceNokia Research Center7 Company Confidential
  • 8. Offline Encounters Influences Online FriendshipSource: Xu et al. Social Linking and Physical Proximity in a Mobile Location-based Service, 1stInternational Workshop on Mobile Location-based Services, In Proc. of UbiComp 2011, 2011Nokia Research Center8 Company Confidential
  • 9. Offline Improves Friend RecommendationSource: Xu et al. Using Physical Context in a Mobile Social Networking Application forImproving Friend Recommendations, 1st International Workshop on Sensing, Networking andComputing on Smartphones, In Proc. of CPSCom 2011, 2011 Nokia Research Center 9 Company Confidential
  • 10. Recording offline interactions as ephemeralsocial networks Offline physical activities (Conf., Meeting, Party, Shopping, Hiking…) Activity 1 Activity 3 Activity 2 Activity n … Online social networks (Facebook, Twitter, Weibo, Renren…)Nokia Research Center time10 Company Confidential
  • 11. Contributions • Create Find & Connect, a platform combining the conference program with indoor location and proximity • Deploy Find & Connect to UbiComp 2011 conference • Understand user behaviour in conference using social network analysis, data mining and survey techniquesNokia Research Center11 Company Confidential
  • 12. Find & Connect @ UbiComp 2011 • Allow conference attendees to connect with each other during the conference based on • their location • Their common research interests • the sessions that they have attended • the attendees that they have encountered over the course of the conference • Common friendsNokia Research Center12 Company Confidential
  • 13. Find & Connect system RFID positioning Find & Connect Mobile device RFID badge RFID readers with LANDMARC server algorithmNokia Research Center13 Company Confidential
  • 14. Find someone nearby during sessionNokia Research Center14 Company Confidential
  • 15. Find who this person is and what youhave in commonNokia Research Center15 Company Confidential
  • 16. Add this person as contactNokia Research Center16 Company Confidential 16
  • 17. See the conference program and whoattended the sessionsNokia Research Center17 Company Confidential 17
  • 18. See notifications of who added you ascontactNokia Research Center Company Confidential 18
  • 19. User behaviour analysis • Demographics • Feature usage • Online connections • Offline encountersNokia Research Center19 Company Confidential
  • 20. Demographics • Sept. 17 to 21, 2011 at Tsinghua University • Workshops, tutorials, research papers, posters, videos, demos • 421 registered attendees, 241 used Find & Connect (57%) • Apple device (31.34%), Google Chrome (23.85%), Android (22.12%), Firefox (9.08%), Internet Explorer (8.29%)Nokia Research Center20 Company Confidential
  • 21. Feature usage • Finding people nearby (11.66%) • Notices (10.30%) • Login (6.27%) • Program (4.97%) • Finding people farther away (3.29%)Nokia Research Center21 Company Confidential
  • 22. Online connections: contacts graphNokia Research Center22 Company Confidential
  • 23. Online connections: contactsNokia Research Center23 Company Confidential
  • 24. Contacts degree distributionNokia Research Center24 Company Confidential
  • 25. Offline is the reason why people add friendsNokia Research Center25 Company Confidential
  • 26. Contact recommendation • Weight vector wi : wi = {wci, wcf, wcs,we, | wci + wcf + wcs +we = 1, 0 < wf < 1} •Relevance vector Ri : Ri = {Rci, Rcf, Rcs, Re} • Relevance Rf Jaccard similarity of that feature f between Ui and U as Rf = | Nf (Ui ∩ U) | / |Nf (Ui U U) | • Recommended score FRi FRi = wi · Ri = {wci, wcf, wcs, we}·{Rci, Rcf, Rcs, Re, }TNokia Research Center26 Company Confidential
  • 27. Contact recommendations results • 15252 total, 309 of them added by 63 users = 2% of all contact recommendations converted into contact requests • Low conversion rate probably due to few people using the recommendations featureNokia Research Center27 Company Confidential
  • 28. Offline connections: encounters graphNokia Research Center28 Company Confidential
  • 29. Offline connections: encounters • 12,716,349 total encountersNokia Research Center29 Company Confidential
  • 30. Encounters degree distributionNokia Research Center30 Company Confidential
  • 31. Implications • Find & Connect can help people build connections in a conference • People add others as friends/contacts if have physically met them • Recommendations need to be more visible in order to be useful • Post survey results show features were useful and user interface as averageNokia Research Center31 Company Confidential
  • 32. Conclusions • Contact and encounter networks follow social influence theory of 3 degrees of separation Cacioppo, J.T., Fowler, J.H., and Christakis, N.A. Alone in the crowd: the structure and spread of loneliness in a large social network. Journal of Personality and Social Psychology, 97, 6 (2009), 977. • Users add others as contacts because of homophily and proximity • encounters • common sessions • common friends • People generally find Find & Connect useful somewhat easy to useNokia Research Center32 Company Confidential
  • 33. Future work • Improve user interface, users can post to online SNS and can add friends to SNS • Study relationship between online and offline • Create model to identify groups of encounters that indicate activity-based social networks (ephemeral social networks)Nokia Research Center33 Company Confidential
  • 34. Alvin Chin Nokia Research Center, Beijing alvin.chin@nokia.com http://research.nokia.com/people/alvin_chin Facebook: Alvin Chin (alvin.chin@utoronto.ca) LinkedIn: alvin.chin@nokia.com Twitter: gadgetman4u Sina Weibo: http://weibo.com/2106762242 (gadgetman) Foursquare: Alvin Chin (alvin.chin@nokia.com) Google+: ubiquitousdude@gmail.comNokia Research Center34 Company Confidential